Conventional FTS systems, based on Michelson interferometers, assume that the radiance of a scene does not vary while the interferogram is being recorded. If the scene radiance does vary, however, as the line of sight (LOS) of the system changes for an inhomogeneous scene, then the radiance spectrum may not be accurate. If the LOS change is random, scene inhomogeity may become a significant contributor to the spectral measurement noise.
In meteorological sounding applications that use FTS systems, the scene inhomogeneity caused by the presence of clouds is a significant source of noise and uncertainty, when trying to measure cloud-free radiances. Conventional retrieval algorithms attempt to remove inhomogeneity by using methods, such as “cloud clearing”, “hole hunting,” or other cloud-masking techniques. None of these methods, however, is able unambiguously to determine the degree of scene inhomogeneity for an individual, or single field of view (FOV) of an FTS system. These FTS systems typically require observations of multiple or adjacent fields-of-view. As a general rule, these observations require a longer period of processing time and more processing throughput.
The deficiencies of conventional methods used to determine the degree of scene inhomogeneity, during observations by FTS systems, show that a need still exists for a method and system which can determine or measure the degree of scene inhomogeneity, using an observation from a single FOV of an FTS system. Eliminating measurements that include scene inhomogeneity could significantly improve the accuracy of sounding algorithms used to retrieve atmospheric parameters of interest. Furthermore, simply knowing that a FOV contains a homogeneous scene permits distinguishing between errors due to scene inhomogeneity and other uncontrollable, or random LOS changes on the measured spectra. The present invention addresses these deficiencies and concerns.